AI is transforming the way employees across the board gain job-ready skills.

We talked with James Della-Porta, Director, Solution Sales - Employee Experience (Australia & New Zealand) at ServiceNow to discuss how  AI can be an asset to companies. We explore the present, and future, of AI in learning and how addressing skill gaps has a new ally. James helps unpack the future of AI-powered learning, its potential to create a more engaging experience, and how it empowers individuals to continuously develop and keep pace with the evolving job market.

Below are the excerpts from our conversation

Q. With skills emerging as a vital business imperative, how can AI assist companies address internal skills gaps? Can you give us examples of its application?

Skills have been important for a long time, but there is a real transition in progress at the moment. The world is changing at a faster rate than ever.  No longer are we training for a career that lasts 30+ years. In fact, a  World Economic Forum report stated that the half life of skills have recently shrunk to just 2.5 years. This is creating tension and imbalance in the equation between skills that are becoming outdated, and future skills that we need to learn.
 
The good news is that technology can assist.  We already have many tools at our disposal, including machine learning, intelligent search, workflows and automation, and now Artificial Intelligence and GenAI.
 
Some of the areas that we see opportunity to help address skills shortages (and there is predicted to be 85 million jobs unfilled by 2030 globally), include improving Talent Mobility, predictive assessments of skills demand and shortages, streamlining and accelerating ramp times for new roles, reducing workloads by deflecting trivial or administrative work or synthesise large amounts of data and information to enable faster decision making.
 

Q. How can AI proactively identify skills needed for upcoming job changes or industry disruptions within a company?

The first thing organisations need to do is to get a baseline of their current skills, deployment and availability. Typically information around skills is siloed, and sometimes not captured at all.  Ideally, this information can be sourced from multiple areas, such as parsing CVs and resumes during recruitment (or from the ATS), taking feeds from the Learning Management System, inferring skills from projects, assignments and capabilities/competencies from your HR Management System, as examples.  Artificial Intelligence can help in a number of these areas. This can be used to build Skills Intelligence within an organisation.

These skills can then be matched against domains to understand current skills, potential gaps and build Employee Growth & Development Plans.
 
Taking things a step further, scanning external sources, such as LinkedIn, job postings, competitive organisations and industries a map of current and future skills in demand can be generated.  Using your Skills Intelligence, you can then scan for 'Hidden Talent' that may be able to service that skills demand, whether they are skills located in other parts of the organisation, or there are adjacent experiences and skills that can be complemented with learning or on the job experience to fill that need.  Another advantage of promoting internal talent mobility is that you retain your institutional knowledge as employees already understand how your organisation works and how to navigate those networks.
 

Q. Can you elaborate on how AI can personalise learning paths to address individual skill gaps and strengths of employees? How else can it make upskilling engaging and interactive for employees?

One of the best ways to improve the adoption of learning, is to seek ways to provide micro learning opportunities or even better, Learning in the Flow of Work.  Gone are the days of locking someone in a classroom and expecting them to pick up the skills that they will need for the next 10 years.  You'd be lucky if they retain 5-10% of that learning, and chances are it would be redundant within 3-5 years anyway.  And quite simply, we are all too busy to carve out that much time.
 
As an example, a virtual agent could identify when a project or assignment is approaching and recommend an applicable short learning course in preparation (and even book it into your calendar for you).  Or using intelligent search, it could pick up on the theme of something an employee is looking for and suggest a knowledge article or exercise/lab to provide a skill that is required at that point in time.
 
You could also have AI design a curated, and personalised learning path based on a career conversation, and assess the gaps between their current skills and experience and their intended goal and the skills required.
 
Making learning more interactive is important to drive consistency and adoption.  This could take the form of offering nudges to someone that might have not sought out or completed learning in a period of time, as well as prompts for micro learning opportunities 'in the flow of work' that are contextualised and relevant to the employee at that point in time.

Gamification is another way that learning can be made more engaging.  This could be encouraged through leaderboards and badges, creating elements with cohort based learning with peers that encompasses live and interactive components.
 

Q. What are benefits of AI for skilling that today make it an invaluable asset for companies? What other features do you see playing a role in the future of learning and development?

One of the things I passionately talk about, is that technology and AI don't need to translate to de-humanising the workplace. In fact, if we do this well, we should be enhancing the elements of our human aspects. This is for a couple of reasons. Firstly, by reducing noise (which there is too much of), low-level tasks, and streamlining work to speed up, simplify or reduce distractions, we can create more space to elevate an employees ability to tap into more purposeful work.  This also has the added benefit of increasing employee engagement.
 
In addition to this, with the increasingly fast changing nature of our world, there is a greater need to rely on very human skills such as adaptability, elasticity (in mindset and approach) and resilience. So my guidance is that AI won't solve all your skills and learning needs.  It can do a lot, but it will also facilitate how we as employees and people can be more empowered to do the work that is highly valued.
 

Q. How can AI-powered learning be made accessible and equitable for all employees, regardless of background or technical skills?

An example of this is how we might move from a fixed job structure to something that is more flexible.  This is increasingly becoming desirable as skills change more rapidly, and demand for new skills heat up.  When demand for a particular skill arises, an AI process could leverage the knowledge and skills intelligence of the workforce to identify candidates that might meet this need.
 
A number of factors could be considered to select someone to either fill this requirement or be presented with a learning opportunity in order to gain the skills to meet this skill demand.  Some of these might be that they already possess this skill, or an adjacent skill, and if they are available.  But we could also program considerations such as diversity, to rank or prioritise candidates to promote a greater distribution of skills in the workplace.
 
Following on from this, an organisation could also set up a structure that rewards and pays based on skills.  Hence providing opportunities for diverse or under-represented backgrounds to acquire those skills can help to address pay imbalances in the workplace.